Journal article
Probabilistic voltage management using OLTC and dSTATCOM in distribution networks
IEEE Transactions on Power Delivery, Vol.33(2), pp.570-580
2017
Abstract
Low voltage (LV) feeder voltage magnitude and unbalance are often the constraining factors on a feeder's capacity to absorb rooftop photovoltaic (PV) generation. This paper presents a new probabilistic method for voltage management in distribution networks through the placement of distribution static compensators (dSTATCOM) and on-load tap changers (OLTC) considering the reactive capability of PV inverters in multiple LV and medium volt-age distribution networks. The method uses a modified particle swarm optimization. In this paper, several scenarios for the place-ments of multiple dSTATCOMs with and without embedded energy storage systems using both reactive and real power compensation are investigated in combination with an OLTC equipped with independent per-phase tap-changing control. The voltage constraints in the proposed method are statistically defined using three duration curves. These are the voltage unbalance, maximum voltage and minimum voltage duration curves. The method is comprehensively tested for varying load and PV generation based on data from a real Australian distribution network with considerable unbalance and distributed PV generation. The results show that PV hosting capacity increases where the proposed approach is applied.
Details
- Title
- Probabilistic voltage management using OLTC and dSTATCOM in distribution networks
- Authors/Creators
- H. Pezeshki (Author/Creator)A. Arefi (Author/Creator)G. Ledwich (Author/Creator)P.J. Wolfs (Author/Creator)
- Publication Details
- IEEE Transactions on Power Delivery, Vol.33(2), pp.570-580
- Publisher
- IEEE
- Identifiers
- 991005544227507891
- Copyright
- 2017 IEEE
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Journal article
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites
Metrics
26 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.18 Power Systems & Electric Vehicles
- 4.18.204 Smart Grid Optimization
- Web Of Science research areas
- Engineering, Electrical & Electronic
- ESI research areas
- Engineering